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Authors: Luis Palacios 1 ; Gaëlle Lortal 2 ; Claire Laudy 2 ; Christian Sannino 3 ; Ludovic Simon 3 ; Giuseppe Fusco 4 ; Yue Ma 4 and Chantal Reynaud 4

Affiliations: 1 Thales Research & Technologies and Laboratoire de Recherche en Informatique (LRI), France ; 2 Thales Research & Technologies, France ; 3 Thales Avionics, France ; 4 Laboratoire de Recherche en Informatique (LRI), France

ISBN: 978-989-758-203-5

Keyword(s): Ontology Building, Ontology Alignment, Evaluation Prototype, Aeronautics, Predictive Maintenance.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Domain Analysis and Modeling ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Ontology Matching and Alignment ; Symbolic Systems

Abstract: In the aviation industry, the delay in maintaining or recovering aircrafts heavily impacts the profit of an airline company. Consequently the maintenance actions identification and planning of aircrafts is crucial. However, due to the complexity of the domain in terms of data sources, distributed systems and information availability, it is hard to provide automatic maintenance support. We propose to use semantic technologies to model the domain at a conceptual level through ontology, thus abstracting from the data sources and the maintenancers’uses and jobs. In this manner the information relevant for characterizing failures and maintenance events is encapsulated and provided to end users via an easier access, which otherwise would be inaccessible or would require expert analysis to obtain. Such a formal model of the domain can furthermore enable automated reasoning for maintenance discovery and failure causes detection by integrating a large amount of background contextual informatio n scattering in different resources. In this paper we provide the rationale of the Avionics Maintenance ontology i.e. how we built it through expert knowledge and alignment of different sources and an ontology alignment evaluation tool. (More)

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Paper citation in several formats:
Palacios, L.; Lortal, G.; Laudy, C.; Sannino, C.; Simon, L.; Fusco, G.; Ma, Y. and Reynaud, C. (2016). Avionics Maintenance Ontology Building for Failure Diagnosis Support.In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016) ISBN 978-989-758-203-5, pages 204-209. DOI: 10.5220/0006092002040209

@conference{keod16,
author={Luis Palacios. and Gaëlle Lortal. and Claire Laudy. and Christian Sannino. and Ludovic Simon. and Giuseppe Fusco. and Yue Ma. and Chantal Reynaud.},
title={Avionics Maintenance Ontology Building for Failure Diagnosis Support},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)},
year={2016},
pages={204-209},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006092002040209},
isbn={978-989-758-203-5},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)
TI - Avionics Maintenance Ontology Building for Failure Diagnosis Support
SN - 978-989-758-203-5
AU - Palacios, L.
AU - Lortal, G.
AU - Laudy, C.
AU - Sannino, C.
AU - Simon, L.
AU - Fusco, G.
AU - Ma, Y.
AU - Reynaud, C.
PY - 2016
SP - 204
EP - 209
DO - 10.5220/0006092002040209

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